Triple
T35240853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bluetongue Stadium |
E1017509
|
entity |
| Predicate | hasWaterfrontLocation |
P186497
|
FINISHED |
| Object | true |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: true | Statement: [Bluetongue Stadium, hasWaterfrontLocation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterfrontLocation Context triple: [Bluetongue Stadium, hasWaterfrontLocation, true]
-
A.
hasWaterfrontType
Indicates that an entity is associated with a specific type or category of waterfront (e.g., oceanfront, lakefront, riverfront).
-
B.
hasWaterfrontAccessTo
Indicates that one entity is directly adjacent to and can physically access a particular body of water, such as a lake, river, or ocean.
-
C.
hasWaterfrontArea
Indicates that an entity possesses or includes an area directly adjacent to or bordering a body of water.
-
D.
hasWaterfrontUse
Indicates that an entity is used, designated, or suitable for activities or purposes directly related to a waterfront or shoreline area.
-
E.
locatedInWaterfrontArea
Indicates that something is situated within a designated waterfront area adjacent to a body of water.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76de235048190b990070c23c51b6b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f9fe1a1ca4819084c196f0041f0be2 |
completed | May 5, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69f7cf769338819092a5f42653dcc956 |
completed | May 3, 2026, 10:43 p.m. |
| PDg | Predicate description generation | batch_69f9fd66eed48190bdc26a8def328c2d |
completed | May 5, 2026, 2:23 p.m. |
Created at: May 3, 2026, 4:02 p.m.